Supporting mobility with steady quality is a requirement for 4th generation (4G) networks and beyond. To this end, handover is a key Radio Resource Management (RRM) technique that ensures service continuity while a user is moving across radio cells by changing attachment of a user terminal from one cell to another more suitable cell, thereby enhancing the user experience and the overall network performances (lower power consumption, lower radio interference, etc).
However, the handover procedure is performed upon triggering conditions which have to be properly configured and optimized so that target Quality of Service (Qos) and Quality of Experience (QoE) objectives are achieved.
Indeed, an efficient design and optimization of the handover procedure shall meet the following requirements:    minimizing Radio Link Failures (RLF) and call drops during handover procedures; while    minimizing the number of unnecessary handovers; and    maximizing the duration of user connection to the best cell.
To illustrate this, let's consider the two following scenarios.    A handover that is triggered too lately leads to RLF in the source cell: the user keeps attached to its serving cell while moving outside the cell radio coverage.    Conversely, a handover that is launched too early leads to erroneous decisions: useless handover decision to a new cell, and then reconnection to the original serving cell (ping-pong handovers), or erroneous selection of a new target cell.
So, it is easy to understand that it is crucial to achieve a fine-adjustment of the handover parameter values in order to trigger a handover when appropriate, and towards a properly selected target cell. When appropriate and towards a properly selected target cell means that the following trade-off between the following—and somehow contradictory—goals is met: minimizing the duration before detection, that is to say the duration between the instant of an effective change (e.g., target cell gets offset-better than current serving cell) and the decision to trigger a handover, while minimizing false handover alarms (i.e., erroneous handover decisions).
In 3rd Generation Partnership Project (3GPP) standard development, the Mobility Robustness Optimization (MRO) feature aims at first detecting and counting RLFs due to handovers, then to find solutions to reduce handover performances degradation.
MRO distinguishes three handover failure cases:    [Too Late HO] A connection failure occurs in the source cell before the handover was initiated, or during a handover; the User Equipment (UE) attempts to re-establish the radio link connection in the target cell (if handover was initiated) or in a cell that is not the source cell (if handover was not initiated).    [Too Early HO] A connection failure occurs shortly after a successful handover from a source cell to a target cell, or during a handover; the UE attempts to re-establish the radio link connection in the source cell.    [HO to Wrong Cell] A connection failure occurs shortly after a successful handover from a source cell to a target cell or during a handover; the UE attempts to re-establish the radio link connection in a cell other than the source cell and the target cell.
In 3GPP Long Term Evolution (LTE) standard, handover is performed as following. The user performs periodic measurements, typically filtered Reference Signal Received Powers (RSRP) on the serving (Ms) and neighbor cells (Mn). When a given handover condition is met (typically an A3 event) for a particular neighboring cell, the UE reports its measurements to the serving cell, which eventually decides to trigger or not a handover based on the user's recommendations.
Basically, A3 event reporting by the UE is triggered if at least one neighbor cell becomes better than the serving cell by a configurable offset value. Handover reporting measurement by the UE is triggered if the condition is met for a minimal configurable duration or Time-To-Trigger (TTT).
Particularly in dense networks of small cells (but not only), it is important to reduce the time for operators to manage a wide set of cell and handover parameters in particular. It is also worthwhile to state that the automatic configuration and optimization of cell and handover parameters is a key feature for 4G networks, especially for dense networks.
We propose a solution to enable each cell, in a distributive and fully autonomous way, to jointly adjust the major handover parameters so as to achieve a near-optimal trade-off between minimizing the probability of late handover decisions (rate of Too Late HO) while minimizing the risk of false alarms (rate of Too Early HO and HO to Wrong Cell).
To the best of our knowledge, there is no solution to jointly optimize the handover parameters.
In the article entitled “A Cost-based Adaptive Handover Hysteresis Scheme to Minimize the Handover Failure Rate in 3GPP LTE System” from D-W Lee, G-T Gil and D-H Kim, and published in July 2010 in the EURASIP Journal on Wireless Communications and Networking, the hysteresis parameter is iteratively adjusted (increased/decreased) so as to minimize handover failure rate, accounting for neighbor cells load, the user speed or the traffic type.
In the conference paper entitled “Handover Parameter Optimization in LTE Self-Organizing Networks” from T. Jansen, I. Balan & al published in September 2010 during the IEEE 72nd Vehicular Technology Conference in Ottawa (Canada), the operating point (Hysteresis or HO Margin, Time-To-Trigger) is adjusted in an iterative way in order to minimize handover related QoS like handover failure ratio, ping-pong (oscillation) rates or call dropping rates. The adjustment path is set-up according to the experienced performances compared to target ones. Although practical, the empirical solutions lack theoretical basis for solving the trade-off introduced here above.
In the conference paper entitled “A Novel Self-optimizing Handover Mechanism for Multi-Service provisioning in LTE-Advanced” from H. Zhang, X. Wen & al published in 2009 during Research Challenges in Computer Science ICRCCS '09 conference, the authors tune hysteresis, Time-To-Trigger and filtering parameters so that the number of handovers gets close to the number of cells boundary crossings. Though novel, this approach does not rely on handover counters specified by 3GPP through MRO feature, which makes its application in real networks difficult.
In the lecture notes entitled “Distributed Self-Optimization of Handover for the Long Term Evolution” from A. Schröder, H. Lundqvist and G. Nunzi published in 2008 in Computing Science, Volume 5343/2008, p. 281-286, the authors presents a trial and error loop method to optimize one or more handover parameters.